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Related papers: Mimicking Networks Parameterized by Connectivity

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We initiate the investigation of the parameterized complexity of Diameter and Connectivity in the streaming paradigm. On the positive end, we show that knowing a vertex cover of size $k$ allows for algorithms in the Adjacency List (AL)…

Data Structures and Algorithms · Computer Science 2024-07-19 Jelle J. Oostveen , Erik Jan van Leeuwen

Markov Networks are widely used through out computer vision and machine learning. An important subclass are the Associative Markov Networks which are used in a wide variety of applications. For these networks a good approximate minimum cost…

Artificial Intelligence · Computer Science 2012-03-19 Chris Russell , L'ubor Ladicky , Pushmeet Kohli , Philip H. S. Torr

Connectivity (or equivalently, unweighted maximum flow) is an important measure in graph theory and combinatorial optimization. Given a graph $G$ with vertices $s$ and $t$, the connectivity $\lambda(s,t)$ from $s$ to $t$ is defined to be…

Data Structures and Algorithms · Computer Science 2024-12-25 Shyan Akmal

We initiate the study of graph algorithms in the streaming setting on massive distributed and parallel systems inspired by practical data processing systems. The objective is to design algorithms that can efficiently process evolving graphs…

Data Structures and Algorithms · Computer Science 2025-01-20 Artur Czumaj , Gopinath Mishra , Anish Mukherjee

We prove essentially tight lower bounds, conditionally to the Exponential Time Hypothesis, for two fundamental but seemingly very different cutting problems on surface-embedded graphs: the Shortest Cut Graph problem and the Multiway Cut…

Computational Complexity · Computer Science 2021-02-18 Vincent Cohen-Addad , Éric Colin de Verdière , Daniel Marx , Arnaud de Mesmay

The classical Menger's theorem states that in any undirected (or directed) graph $G$, given a pair of vertices $s$ and $t$, the maximum number of vertex (edge) disjoint paths is equal to the minimum number of vertices (edges) needed to…

Data Structures and Algorithms · Computer Science 2015-09-21 Ashutosh Rai , M. S. Ramanujan , Saket Saurabh

Graph Sparsification aims at compressing large graphs into smaller ones while preserving important characteristics of the input graph. In this work we study Vertex Sparsifiers, i.e., sparsifiers whose goal is to reduce the number of…

Data Structures and Algorithms · Computer Science 2017-12-29 Gramoz Goranci , Monika Henzinger , Pan Peng

MaxCut is a classical NP-complete problem and a crucial building block in many combinatorial algorithms. The famous Edwards-Erd\H{o}s bound states that any connected graph on n vertices with m edges contains a cut of size at least $m/2 +…

Data Structures and Algorithms · Computer Science 2024-07-02 Jonas Lill , Kalina Petrova , Simon Weber

In this note we describe an application of low-high orders in fault-tolerant network design. Baswana et al. [DISC 2015] study the following reachability problem. We are given a flow graph $G = (V, A)$ with start vertex $s$, and a spanning…

Data Structures and Algorithms · Computer Science 2015-11-25 Loukas Georgiadis , Robert E. Tarjan

We consider the problem of finding small distance-preserving subgraphs of undirected, unweighted interval graphs with $k$ terminal vertices. To start with, we show that finding an optimal distance-preserving subgraph is $\mathsf{NP}$-hard…

Data Structures and Algorithms · Computer Science 2018-09-27 Kshitij Gajjar , Jaikumar Radhakrishnan

Given an undirected, edge-weighted graph G together with pairs of vertices, called pairs of terminals, the minimum multicut problem asks for a minimum-weight set of edges such that, after deleting these edges, the two terminals of each pair…

Data Structures and Algorithms · Computer Science 2016-11-24 Éric Colin de Verdière

Graph convolutional networks (GCNs) are powerful deep neural networks for graph-structured data. However, GCN computes the representation of a node recursively from its neighbors, making the receptive field size grow exponentially with the…

Machine Learning · Statistics 2018-03-02 Jianfei Chen , Jun Zhu , Le Song

Quantum circuits composed of CNOT and $R_z$ are fundamental building blocks of many quantum algorithms, so optimizing the synthesis of such quantum circuits is crucial. We address this problem from a theoretical perspective by studying the…

Quantum Physics · Physics 2025-09-15 Yixin Cao , Yiren Lu , Junhong Nie , Xiaoming Sun , Guojing Tian

In the recent research of data mining, frequent structures in a sequence of graphs have been studied intensively, and one of the main concern is changing structures along a sequence of graphs that can capture dynamic properties of data. On…

Data Structures and Algorithms · Computer Science 2012-06-28 Takeaki Uno , Yushi Uno

A matching cut in a graph G is an edge cut of G that is also a matching. This short survey gives an overview of old and new results and open problems for Maximum Matching Cut, which is to determine the size of a largest matching cut in a…

Combinatorics · Mathematics 2023-12-21 Van Bang Le , Felicia Lucke , Daniël Paulusma , Bernard Ries

We consider the minimum cut problem in undirected, weighted graphs. We give a simple algorithm to find a minimum cut that $2$-respects (cuts two edges of) a spanning tree $T$ of a graph $G$. This procedure can be used in place of the…

Data Structures and Algorithms · Computer Science 2020-06-11 Nalin Bhardwaj , Antonio Molina Lovett , Bryce Sandlund

We introduce and study Weighted Min $(s,t)$-Cut Prevention, where we are given a graph $G=(V,E)$ with vertices $s$ and $t$ and an edge cost function and the aim is to choose an edge set $D$ of total cost at most $d$ such that $G$ has no…

Data Structures and Algorithms · Computer Science 2021-07-12 Niels Grüttemeier , Christian Komusiewicz , Nils Morawietz , Frank Sommer

Given a graph $G=(V,E)$ on $n$ vertices and an integer $k$ between 1 and $n-1$, the $k$-token graph $F_k(G)$ has vertices representing the $k$-subsets of $V$, and two vertices are adjacent if their symmetric difference is the two…

Combinatorics · Mathematics 2024-12-31 X. Song , C. Dalfó , M. A. Fiol , S. Zhang

Node embedding is the task of extracting concise and informative representations of certain entities that are connected in a network. Various real-world networks include information about both node connectivity and certain node attributes,…

Social and Information Networks · Computer Science 2022-02-24 Charilaos I. Kanatsoulis , Nicholas D. Sidiropoulos

One of the most important and well-studied settings for network design is edge-connectivity requirements. This encompasses uniform demands such as the Minimum $k$-Edge-Connected Spanning Subgraph problem ($k$-ECSS), as well as nonuniform…

Data Structures and Algorithms · Computer Science 2022-06-27 Michael Dinitz , Ama Koranteng , Guy Kortsarz